Effects of Aging on Patellofemoral Joint Stress during Stair Negotiation on Challenging Surfaces
1
Department of Kinesiology, Boise State University, Boise, ID 83725, USA
2
Department of Mechanical and Biomedical Engineering, Boise State University, Boise, ID 83725, USA
*
Author to whom correspondence should be addressed.
Biomechanics 2024, 4(3), 507-519; https://doi.org/10.3390/biomechanics4030036
Submission received: 15 June 2024
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Revised: 2 August 2024
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Accepted: 16 August 2024
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Published: 2 September 2024
(This article belongs to the Special Issue Personalized Biomechanics and Orthopedics of the Lower Extremity)
Abstract
:This study examined the effect of age and surface on patellofemoral joint (PFJ) stress magnitude and waveform during stair ascent and descent tasks. A total of 12 young and 12 older adults had knee biomechanics quantified while they ascended and descended stairs on normal, slick, and uneven surfaces. The peak of stance (0–100%) PFJ stress and associated components were submitted to a two-way repeated measures ANOVA, while the PFJ stress waveform was submitted to statistical parametric mapping two-way ANOVA. During stair ascent, older adults exhibited greater PFJ stress waveforms, from 55 to 59% and 74 to 84% of stance (p < 0.001) as well as greater PFJ stress–time integral across stance (p = 0.003), and later peak PFJ stress, than young adults (p = 0.002). When ascending on the uneven surface, participants exhibited smaller PFJ stress from 9 to 24% of stance compared to the normal surface, but greater PFJ stress from 75 to 88% and from 63 to 68% of stance (p < 0.001) as well as greater PFJ stress–time integrals compared to normal and slick surfaces (p < 0.032). During stair descent, older adults exhibited a smaller PFJ contact area range (p = 0.034) and peak knee flexion angle (p = 0.022) than young adults. When descending on the slick surface, participants exhibited smaller PFJ stress from 5 to 18% of stance, but greater stress, from 92 to 98% of stance (both: p < 0.001), compared to the normal surface. Negotiating slick and uneven stairs may produce knee biomechanics that increase PFJ stress, and the larger, later PFJ stress exhibited by older adults may further increase their risk of PFJ pain.
1. Introduction
Nearly 60% of older adults (over 65 years) suffer musculoskeletal pain [1]. Yet, this pain is undertreated and underreported, as there is a false belief it is associated with normal aging [2]. Patellofemoral joint (PFJ) pain is an overuse lower limb musculoskeletal disorder that affects approximately 23% of adults, which may not be properly treated or accurately reported in older adults [3]. Although elevated incidence of PFJ pain is evident at 30–49 years and continually increases until 60 years of age [4], older adult PFJ pain prevalence remains relatively unknown. Considering the fact that older adults may experience a disproportionate amount of PFJ pain, identifying the abnormal knee biomechanics that increase their likelihood of developing this debilitating condition would improve treatment, increase mobility, and prevent quality of life decrements [5].
Patellofemoral joint pain reportedly develops from repeated application of elevated forces, or stress, on the joint’s articular cartilage. Traditionally, PFJ stress is reported as intensity (i.e., peak magnitude) or stress vs. time profiles (i.e., stress–time integral). Although this provides key insight into tissue damage that leads to PFJ pain [6], experimental evidence exploring differences between PFJ pain and healthy individuals is inconclusive. Individuals with PFJ pain tend to exhibit knee biomechanics that both decrease and increase PFJ stress. Specifically, these individuals walk slower resulting in smaller peak vertical ground reaction force and peak knee extension moment to limit PFJ stress, while also reducing the knee flexion angle resulting in a reduction in the PFJ contact area and a subsequent increase in PFJ stress compared to healthy individuals [7,8]. However, despite exhibiting knee biomechanical adaptations that may both increase and decrease PFJ stress, individuals with PFJ pain exhibit larger increases in peak PFJ stress and stress–time values (greater than 200%) than healthy individuals [7]. Older adults exhibit similar knee biomechanics compared to individuals with PFJ pain during walking and may be subjected to similar increases in PFJ stress; however, current PFJ stress analysis remains quite limited. Presently, traditional PFJ stress (i.e., discrete peak and stress–time integral) measures fail to identify how biomechanical differences lead to increases in stress and pain at the joint and when these differences occur during the gait cycle. Considering older adults may be vulnerable to PFJ pain, temporal and waveform analysis (i.e., time of peak and local peaks) of their knee biomechanics may provide insight into how aging increases the likelihood of PFJ pain.
Older adults reportedly walk slower with a flexed knee and greater muscular activation, but smaller peak knee extension moment, than their younger counterparts [9,10]. These adaptations may compensate for aging-related reductions in lower limb strength and joint stability and theoretically reduce PFJ reaction force and subsequent joint stress [11,12]. Conversely, normal age-related cartilage degeneration reduces PFJ contact area leading to substantial increases in older adult PFJ stress [13]. When walking, older adults exhibit substantial increases in quadriceps contraction in late stance, which may lead to concurrent increases in PFJ stress–time profiles [14]. Yet, it is currently unknown whether older adults exhibit greater magnitudes or temporal differences in PFJ stress compared to their younger counterparts.
Negotiating stairs (both ascending and descending) is more physically demanding than level walking [15]. At the knee, a stair ascent and descent require 50% more flexion range of motion and 50% greater peak knee extension moment compared to level walking [15,16]. This results in two to four times greater PFJ stress and stems from large increases in peak PFJ reaction force and knee joint moments to safely negotiate stairs [17]. Age-related decreases in muscle strength can result in maladaptive increases in lower limb joint moments in general, and knee extension moment specifically, to safely negotiate stairs [18]. Yet, navigating stairs with a challenging surface, such as a slick or uneven surface, may further increase PFJ stress. When navigating a slick or uneven surface, individuals, particularly older adults, tend to walk slower with shorter, more variable strides, and increase muscle activation to provide stability to prevent a fall or joint injury [19,20]. Adoption of this “cautious” gait strategy by older adults is multifaceted and may be attributed to a combination of reduced joint sense, poor neuromuscular function, or previous falling experience [21]. Although older adults exhibit greater changes in knee flexion when navigating a challenging surface than their younger counterparts, which may further increase PFJ stress [22], the effect of slick and uneven surfaces on PFJ stress during stair negotiation remains largely unknown. Therefore, this study investigated the effect of age and surface on PFJ stress during stair negotiation. We hypothesize that older adults will exhibit significant differences in PFJ stress waveform, but not magnitude, compared to young adults, and all participants will increase PFJ stress magnitude, but not alter the waveform when ascending and descending stairs with challenging surfaces.
2. Materials and Methods
Twenty-four adults (12 young: 18–25 years of age, and 12 older: over 65 years of age with at least one self-reported accidental fall in the last 12 months) participated (Table 1). Participants who self-reported the following were excluded: (1) previous back or lower extremity injury or surgery, (2) current (in the past six months) back or lower extremity pain or injury, and/or (3) known neurological disorder. Participants in each cohort were matched by sex, height, and body mass index (Table 1). Prior to testing, each participant provided written consent and research approval was obtained from the local Institutional Review Board.
For testing, each participant performed a stair ascent and descent task across three surfaces. During each task, participants had three-dimensional (3D) lower limb (hip, knee, and ankle) biomechanical data recorded with one force platform embedded underneath the target step (2400 Hz, AMTI OR6 Series, Advanced Mechanical Technology Inc., Watertown, MA, USA) and ten high-speed optical cameras (240 Hz, Vantage, Vicon Motion Systems, Ltd., Oxford, UK). For each task, the participant walked at a predetermined, self-selected speed to either ascend or descend two stairs (18.5 cm rise, height determined according to [23]) fixated atop the force platform. For the stair ascent task, participants walked through the motion capture volume and placed their dominant limb on the target (first) step before ascending to the second step. For the stair descent task, participants started on the second step, and descended the stairs by placing their dominant limb on the target (first) stair and then walked through the motion capture volume at the self-selected speed. A participant’s self-selected walk speed was determined from the average time recorded by two sets of infrared timing gates (TracTronix TF100, TracTronix Wireless Timing Systems, Lenexa, KS, USA) as they walked at a comfortable speed through the motion capture volume (about 10 m) five times. Participant foot dominance was determined by asking which foot they would prefer to use to kick a ball [24]. To prevent an accidental fall, participants wore a safety harness connected to an overhead gantry that spanned the motion capture volume. To avoid bias and confounding data, a Latin Square Design was used to randomly assign the task and surface order prior to testing.
Participants performed each stair negotiation task on three different surfaces (1: normal, 2: slick, and 3: uneven) fixed atop each stair (see Appendix A). The normal surface consisted of a flat, painted wood panel. The slick surface consisted of a wood panel covered by a smooth, plastic material that, when combined with the slick booties each participant was required to wear, produced a coefficient of static friction between the shoes and surface (0.19) comparable to ice (0.10) [25]. The uneven surface consisted of a wood panel composed of nine painted wooden blocks of differing heights. Participants performed three successful trials across each surface for each stair negotiation task (ascent and descent). A successful trial required the participant to walk within ±5% of self-selected speed, only contact the target stair with the dominant limb, and not slip or trip during the trial.
During each trial, lower limb biomechanical data was quantified from the 3D coordinates of 50 retro-reflective and four virtual markers using Visual 3D (v6, C-Motion, Inc., Germantown, MD, USA) (see Appendix B). For each trial, synchronous ground reaction force (GRF) and marker trajectory data were low pass filtered using a fourth-order Butterworth filter (12 Hz) and then processed in Visual 3D to calculate 3D knee rotations, forces, and moments using a joint coordinate systems approach [26]. All biomechanical data were normalized from 0% to 100% of the stance phase and resampled to 1% increments (N = 101). The stance phase was identified as from heel strike to toe-off and defined as the moments when GRF first exceeded and fell below 25 N, respectively.
Custom MATLAB (R2021b, Mathworks, Natick, MA, USA) code calculated stance phase PFJ stress using a two-dimensional biomechanical model, according to [17]. The model inputs included knee joint flexion angle and extension moment obtained from data collection, and quadriceps lever arm, a constant (k, that represents the ratio of patellofemoral compression force and the quadriceps force as a function of knee flexion angle), and PFJ contact area obtained from previous experimental data [27,28,29,30]. Specifically, the quadriceps effective lever arm and force were determined using knee joint flexion angle and extension moment, and then used to calculate k and estimate PFJ reaction force. Then, the PFJ contact area was calculated as a function of knee angle and used to determine PFJ stress as the ratio of PFJ reaction force and contact area (further detail in Appendix C).
Predefined knee biomechanics related to PFJ stress were submitted for statistical analysis. Specifically, peak of stance (0–100%) knee flexion joint angle and moment; average and range (peak minus minimum) PFJ contact area; peak and impulse PFJ reaction force; peak, time of peak, and time integral of PFJ stress; and knee flexion angle at peak PFJ stress were averaged across the three successful trials to create a participant-based mean. Then, each participant-based mean was submitted to a two-way repeated measures ANOVA to test the main effects of, and interaction between, age (young vs. old) and surface (normal, slick, and uneven). Significant interactions were submitted to simple effects analysis and a Bonferroni correction was used for significant pairwise comparisons [31]. The effect size was calculated for all significant main effects and interactions using partial eta squared (η2) and pairwise comparisons using Cohen’s d (d) [32,33,34]. Participant demographics were submitted to independent t-tests to identify cohort differences. Alpha was set at p < 0.05 and analysis was performed using SPSS v25 software (IMB, Armonk, NY, USA).
Statistical Parametric Mapping (SPM), a technique for statistically understanding one-dimensional temporal/spatial regions where significant differences may occur, was used to analyze the PFJ stress waveform. Specifically, a two-way repeated measures SPM ANOVA was used to determine the main effects of, and interaction between, age and surface. If the scalar output statistic (SPM{F}) crossed the critical threshold for statistical significance at any time point, a supra-threshold was defined and the associated p-values were calculated using Random Field Theory [35,36]. If a supra-threshold cluster was found, follow-up SPM t-tests (SPM{t}) (p < 0.05) were performed to identify changes within each main effect or interaction. All SPM analysis was conducted in a custom MATLAB code implementing functions from the open-source spm1d package (www.spm1d.org (accessed on 16 February 2022)).
3. Results
The cohorts differed in age (p < 0.001), but not height (p = 0.674), weight (p = 0.394), BMI (p = 0.092), or walk speed (p = 0.720) (Table 1).
3.1. Stair Ascent
There was a significant age-by-surface interaction for time of peak PFJ stress (p = 0.012, η2 = 0.183) and knee flexion at peak PFJ stress (p = 0.003, η2 = 0.228) (Table 2 and Table 3). Older adults exhibited later peak PFJ stress (all: p < 0.037, d > 0.906) and less knee flexion at peak PFJ stress on every surface (all: p < 0.029, d > 0.990) than young adults. In the older adults, peak PFJ stress occurred later on the uneven surface compared to normal and slick surfaces (both: p < 0.008, d > 0.762), while young adults exhibited no difference in time of peak PFJ stress on any surface (p > 0.05). Young adults exhibited greater knee flexion at peak PFJ stress on the uneven compared to the slick surface (p = 0.013, d = 0.98), whereas older adults exhibited no difference in knee flexion at peak PFJ stress on any surface (p > 0.05).
Older adults exhibited greater PFJ stress–time integrals (p = 0.003, η2 = 0.335), PFJ reaction force impulses (p = 0.003, η2 = 0.335), later peak PFJ stresses (p = 0.002, η2 = 0.357), and less knee flexion at peak PFJ stress (p = 0.003, η2 = 0.337) than young adults (Table 2 and Table 3, and Figure 1). No other PFJ measure or any knee flexion biomechanics differed between cohorts (p > 0.05) (Table 2 and Table 3, and Figure 2).
Surface impacted every PFJ measure (all: p < 0.05, η2 > 0.217), except peak PFJ stress (p = 0.230) (Table 2). Participants exhibited greater PFJ stress–time integrals, PFJ reaction force impulses, and PFJ contact areas (both mean and range) on the uneven compared to the normal and slick surfaces (all: p < 0.032, d > 0.297). The surface impacted the peak knee flexion angle (p < 0.001, η2 = 0.095) and extension moment (p = 0.002, η2 = 0.253) (Table 3). Participants exhibited greater peak knee flexion angle on the uneven compared to the normal surface (p < 0.001, d = 0.113), and greater peak knee extension moment on the uneven compared to the slick surface (p = 0.004, d = 0.447) (Table 3).
SPM analysis revealed a main effect of age (p < 0.037) and surface (p < 0.001) for the PFJ stress waveform (Figure 1). Older adults exhibited greater PFJ stress, from 55 to 59% and from 74 to 84% of stance, compared to young adults (p = 0.037, p = 0.004, respectively). On the uneven surface, participants exhibited smaller PFJ stress, from 9 to 24% of stance, but greater PFJ stress, from 75 to 88% of stance, compared to the normal surface (both: p < 0.001), and greater PFJ stress, from 63 to 68% of stance, compared to the slick surface (p = 0.003).
3.2. Stair Descent
Older adults exhibited a smaller PFJ contact area range (p = 0.034, η2 = 0.189) and peak knee flexion angle (p = 0.022, η2 = 0.216) than young adults (Table 3 and Table 4, and Figure 3). No significant difference (p > 0.05) between young and older adults was observed for any other PFJ measure or peak knee extension moment.
The surface impacted the PFJ stress–time integral, PFJ reaction force impulse, and mean PFJ contact area (all: p < 0.002, η2 > 0.249), as well as the peak knee extension moment (p = 0.003, η2 = 0.256) and knee flexion at peak PFJ stress (p = 0.033, η2 = 0.143) (Table 3 and Table 4, and Figure 3). On the uneven surface, participants exhibited greater PFJ stress–time integrals, PFJ reaction force impulses, and mean PFJ contact areas compared to the slick surface (all: p < 0.05, d > 0.370). Peak knee extension moment and mean PFJ contact area were greater on the uneven compared to the normal and slick surfaces (all: p < 0.029, d > 0.394), while knee flexion at peak PFJ stress was greater on the slick compared to the normal surface (p = 0.041, d = 0.81) (Table 3 and Table 4).
SPM analysis revealed a main effect of surface (all: p < 0.014), but not age (p > 0.05), on the PFJ stress waveform (Figure 1). On the uneven surface, participants exhibited greater PFJ stress, from 0 to 16% and 9 to 10% stance (p < 0.001; p = 0.016), but smaller stress, from 98 to 100% and 99 to 100% stance (p = 0.014; p = 0.017), compared to the slick and normal surfaces, respectively. On the slick surface, participants exhibited smaller PFJ stress, from 5 to 18% of stance (p < 0.001), but greater PFJ stress, from 92 to 98% stance, compared to the normal surface (p = 0.002).
4. Discussion
Older adults exhibited a PFJ stress waveform that may increase their risk of pain development. In agreement with our hypothesis, during the stair ascent, older adults exhibited greater PFJ stress, from 55 to 59% and 74 to 84% of stance (i.e., mid to late stance), which stems from the 98% increase in PFJ stress–time integral and significantly later peak PFJ stress they exhibited compared to their younger counterparts. The larger, later PFJ stress may increase older adults’ risk of pain, as it is reportedly exhibited by individuals with confirmed PFJ pain and damages the joint’s articular cartilage, predisposing the individual to pain [37,38]. Although non-significant, the 14% increase in older adult peak PFJ stress during the stair ascent may further load their articular cartilage and stem from the approximate 8 degrees less knee flexion they exhibited at peak PFJ stress compared to young adults. The smaller knee flexion exhibited by older adults would subsequently decrease the PFJ contact area and potentially contribute to their insignificant increase in peak PFJ stress during the stair ascent [7,8]. However, the reason older adults exhibited differences in the PFJ stress waveform, and not in peak PFJ stress, is not immediately evident. Considering peak PFJ stress is purportedly related to peak knee flexion biomechanics [7], the fact that no age dimorphism in peak knee flexion angle and moment was currently observed during the stair ascent may contribute to the insignificant difference in peak PFJ stress. Future work, nonetheless, is warranted to determine if waveform differences in knee flexion biomechanics contribute to magnitude and waveform differences in PFJ stress.
Significant age differences in PFJ stress were not observed during the stair descent. Contrary to our hypothesis, older adults exhibited non-significant 17% and 31% increases in peak PFJ stress and stress–time integral during the stair descent. While the reason the large increases in older adult PFJ stress did not reach statistical significance is not immediately evident, it may be attributed to the large variability exhibited by the current participants, particularly the older adults. During the stair descent, older adults’ coefficient of variation, or measure of relative variability [39], for peak PFJ stress and stress–time integral, was 45 and 51% and was approximately 16% greater than the young adults. In general, older adults exhibit more variable gait due to age-related alterations in musculoskeletal, cognitive, and sensorimotor function than their younger counterparts [40]. The current older adult’s age-related losses of quadriceps strength contribute to both the large PFJ stress variability and specific knee biomechanics alterations exhibited during stair negotiation (see Supplementary Material from [41]). Older adults exhibited a 2-degree reduction in peak knee flexion angle and a 7% decrease in the range of PFJ contact area during the stair descent. Both the reduction in knee flexion angle and PFJ contact area are biomechanical alterations reported to increase PFJ stress, and articular cartilage damage [11]. Yet, weaker older adults may adopt these strategies to prevent limb collapse when descending stairs, as a more extended limb is a biomechanical adaptation to prevent overwhelming the quadriceps musculature [42]. The extended limb, however, is also a weight avoidance strategy and may be adopted by older adults to manage pain. However, considering our participants self-reported no lower limb pain, further study is needed to determine the link between the extended limb and pain management during stair descent.
The challenging surfaces, particularly the uneven surface, impacted PFJ stress and knee flexion biomechanics during stair ascent. On the uneven surface, participants decreased PFJ stress during weight acceptance (from 9 to 24% of stance), but increased stress during terminal stance (from 75 to 88% of stance) when ascending stairs. Both changes can be attributed to specific knee biomechanics adopted by the participants. Participants exhibited 7% greater peak knee flexion as well as a 13% larger PFJ contact area range on the uneven compared to the normal surface. The greater knee flexion would increase the quadriceps mechanical advantage, or reduce the quadriceps force required to produce the knee extensor torque necessary to prevent limb collapse during stair ascent, while a larger PFJ contact area would disperse the quadriceps force across more of the PFJ’s surface, decreasing likelihood of damage [11,43,44]. Both adaptations aid the participants’ ability to limit the magnitude of PFJ stress and contribute to the observed reduction during weight acceptance. Conversely, participants exhibited a 13% increase in both PFJ stress–time integral and PFJ reaction force impulse on the uneven compared to normal surface. The larger PFJ stress integral and reaction force contribute to the elevated joint stress during terminal stance as well as the likelihood of pain development, particularly for older adults. On the uneven surface, the older adults exhibited a 53% later peak PFJ stress compared to the young adults, and a 27% later peak stress compared to the normal and slick surfaces. Older adults with delayed peak PFJ stress may elevate their joint stress in the terminal stance and apply greater force to associated articular cartilage during those gait phases. Yet, future work is needed to determine if the delayed peak PFJ stress exhibited by older adults further increases pain risk.
The challenging surfaces also impacted PFJ stress during stair descent and had the potential to damage the joint’s articular cartilage. Although no significant difference in peak PFJ stress was observed during stair descent due to surface, both the uneven and slick surfaces elicited changes in PFJ stress waveform. When descending on the uneven surface, participants exhibited larger PFJ stress in the early stance (from 0 to 16%) and smaller stress in the late stance (from 98 to 100%) compared to the slick surface. These waveform alterations on the uneven compared to the slick surface result from a 15% increase in PFJ stress–time integral and reaction force impulse. Interestingly, on the uneven surface, participants also exhibited a 15% increase in PFJ reaction force impulse compared to on the normal surface, but no significant difference in PFJ stress peak or waveform compared to on the normal surface. Conversely, on the slick surface, participants exhibited greater knee flexion at peak PFJ stress, which may afford them the ability to limit PFJ stress in the early stance (from 5 to 18%), but required greater stress in the late stance (from 92 to 98%) compared to on the normal surface. Regardless, no differences in discrete PFJ stress variables were observed on the slick compared to on the normal surface. The increases in PFJ stress–time integral and reaction force observed when navigating the challenging surfaces during the stair descent may load the joint’s articular cartilage, leading to degradation and subsequent pain [37,38]. However, further study is needed to determine the effect of greater stress–time integrals on tissue damage and PFJ pain development.
This study may be limited by the PFJ stress calculation. The current PFJ stress model may underestimate PFJ reaction force and subsequent stress, as the model does not account for hamstring muscle force. Considering that van Eijden et al. and Connolly et al. [27,28,29,30] reported r2 values of 0.99 for the predicted PFJ reaction force and estimated PFJ contact area with cadaveric and radiographically derived measures, we are confident that our PFJ stress measures accurately represent PFJ loading. Yet, future work should consider evaluating electromyography of knee musculature to better understand muscle-related factors for PFJ stress during load-bearing activities. Another limitation may include the subject demographics used for this study, particularly weight. Despite attempting to match cohorts by BMI, the older adults had an insignificant 10% larger BMI, which may impact PFJ loading compared to the young adults and future studies may want to normalize PFJ stress by participant body weight. Further, the chosen challenging surfaces may be a limitation. Although the coefficient of friction of the slick surface was comparable to ice (0.19 vs. 0.10), it may not elicit a similar compensatory response as real ice, and the staggered wooden blocks of the uneven surface may be predictable and not imitate the randomness of real-world uneven terrain. Furthermore, we did not control participant footwear, and it is feasible that the shoe–surface interaction differed between participants; but, considering we are unaware of any literature that suggests shoes impact PFJ stress, we are confident in our outcome measures.
In conclusion, older adults are more likely to exhibit knee biomechanics related to PFJ pain development when navigating stairs, particularly late in stance and on uneven surfaces. Older adults exhibited larger, later PFJ stress when ascending, but not descending, the stairs compared to their younger counterparts. These increases in PFJ stress may load the joint’s articular cartilage and predispose older adults to PFJ pain development. Yet, all participants, regardless of age, exhibited alterations in knee biomechanics that may lead to greater PFJ stress when negotiating stairs with slick and uneven surfaces.
Author Contributions
Conceptualization, C.K.F. and T.N.B.; methodology, N.L.H., A.E.H., C.K.F. and T.N.B.; validation, N.L.H., A.E.H., C.K.F. and T.N.B.; formal analysis, N.L.H., A.E.H., C.K.F. and T.N.B.; investigation, N.L.H., A.E.H., C.K.F. and T.N.B.; resources, C.K.F. and T.N.B.; data curation, N.L.H., A.E.H., C.K.F. and T.N.B.; writing—original draft preparation, N.L.H. and T.N.B.; writing—review and editing, N.L.H., A.E.H., C.K.F. and T.N.B.; visualization, N.L.H. and T.N.B.; supervision, C.K.F. and T.N.B.; project administration, C.K.F. and T.N.B.; funding acquisition, C.K.F. and T.N.B. All authors have read and agreed to the published version of the manuscript.
Funding
This study was supported by grants from the NIH National Institute on Aging (R15AG059655) and NIH Institutional Development Awards (IDeA) from the National Institute of General Medical Sciences (P20GM109095, P20GM148321, P20GM103408), and a fellowship from the Boise State University Graduate College.
Institutional Review Board Statement
This study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Boise State University (Protocol Number: 126-MED18-014).
Informed Consent Statement
Written informed consent has been obtained from the patients to publish this paper.
Data Availability Statement
The data presented in this study are openly available in the following data repository [doi: 10.18122/cobr_data.5.boisestate].
Conflicts of Interest
None of the authors demonstrate any conflicts of interest.
Appendix A. Challenging Surfaces
Figure A1.
Depicts normal (A), slick (B), and uneven (C) surfaces fixed on the target and top stair of the staircase (D).
Figure A1.
Depicts normal (A), slick (B), and uneven (C) surfaces fixed on the target and top stair of the staircase (D).
Appendix B. Whole Body Marker Set
Table A1.
Retro-reflective and Virtual Marker Placement for Biomechanical Model.
| Markers | |
|---|---|
| Head | Front, back, left, and right head |
| Trunk | Acromion process, jugular notch, xiphoid process, C7 vertebrae, T10 vertebrae |
| Arm | Medial and lateral wrist and elbow, forearm, and hand |
| Pelvis | Anterior–superior iliac spines, posterior–superior iliac spines, and iliac crests |
| Thigh | Greater trochanter, distal thigh, medial and lateral femoral epicondyles |
| Shank | Tibial tuberosity, lateral fibula, distal tibia, medial and lateral malleoli |
| Foot | Posterior heel, first and fifth metatarsal heads |
Note: Italic indicates calibration markers. Bold indicates virtual markers.
Appendix C. Patellofemoral Joint Stress Model
Stance phase PFJ stress was calculated as a function of knee flexion joint angle and knee extension joint moment based on a two-dimensional biomechanical model according to [17]. Specifically, the model inputs are knee joint flexion angle and extension moment obtained from data collection, and quadriceps lever arm, a constant (k), and PFJ contact area obtained from previous experimental data [27,28,29,30]. First, the quadriceps effective lever arm (LA; fit (r2 = 0.99) to data of [29]) and quadriceps force (QF) were determined using Equations (A1) and (A2):
LA(x) = (8.0 × 10−5 x3 − 1.3 × 10−2 x2 + 2.8 × 10−1 x + 0.046)
QF(x) = MEXT(x)/LA(x)
LA = effective quadriceps lever arm (m), x = flexion angle (rad),
QF = quadriceps force (N), and MEXT = knee extension moment (N × m)
Next, the PFJ reaction force was estimated from a constant (k; fit (r2 = 0.99) to data of [27,28]) that represents the ratio of patellofemoral compression force and the quadriceps force as a function of knee flexion angle, using Equations (A3) and (A4):
k(x) = (4.62 × 10−1 + 1.47 × 10−3 x − 3.84 × 10−5 x2)/(1 − 1.62 × 10−2 x + 1.55 × 10−4 x2 − 6.98 × 10−7 x3)
PFJRF(x) = k(x) × QF(x);
k = constant (N/N), x = knee flexion angle (deg),
PFJRF = PFJ reaction force (N), and QF = quadriceps force (N).
Finally, contact area was calculated as a function of knee angle and PFJ stress was determined as the ratio of PFJ reaction force and contact area (PFJCA: fit (r2 = 0.99) to data of [30]) using Equations (A5) and (A6):
PFJCA(x) = (7.81 × 10−2 x2 + 6.763 × 10−1 x + 151.75)
PFJ Stress(x) = PFJRF(x)/PFJCA(x)
PFJCA = PFJ contact area (mm2), x = knee flexion angle (deg),
PFJ Stress = PFJ stress (N/mm2 or MPa),
PFJRF = PFJ reaction force (N).
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Figure 1.
Mean ± SD stance phase (0–100%) PFJ stress during the stair ascent and descent tasks for young and older adults (A,C) and on each surface (B,D). The grey shaded area depicts significant waveform differences identified by the SPM analysis.
Figure 1.
Mean ± SD stance phase (0–100%) PFJ stress during the stair ascent and descent tasks for young and older adults (A,C) and on each surface (B,D). The grey shaded area depicts significant waveform differences identified by the SPM analysis.
Figure 2.
Mean ± SD stance phase (0–100%) knee flexion angle and knee extension moment during the stair ascent for young and older adults (A,C) and on each surface (B,D).
Figure 2.
Mean ± SD stance phase (0–100%) knee flexion angle and knee extension moment during the stair ascent for young and older adults (A,C) and on each surface (B,D).
Figure 3.
Mean ± SD stance phase (0–100%) knee flexion angle and knee extension moment during the stair descent for young and older adults (A,C) and on each surface (B,D).
Figure 3.
Mean ± SD stance phase (0–100%) knee flexion angle and knee extension moment during the stair descent for young and older adults (A,C) and on each surface (B,D).
Table 1.
Mean (SD) subject demographics for each cohort (young and older adults).
| N | Age (yrs) * | Height (m) | Weight (kg) | Walk Speed (m/s) | |
|---|---|---|---|---|---|
| Young | 12 | 21.08 (1.93) | 1.75 (0.10) | 68.91 (16.86) | 1.06 (0.83) |
| Older | 12 | 69.92 (3.15) | 1.73 (0.13) | 75.05 (17.71 | 1.04 (0.17) |
* Denotes a significant (p < 0.05) effect of age.
Table 2.
Mean (SD) for PFJ measures during stair ascent for young and older adults on each surface (normal, uneven, and slick).
Table 2.
Mean (SD) for PFJ measures during stair ascent for young and older adults on each surface (normal, uneven, and slick).
| Normal | Uneven | Slick | ||||
|---|---|---|---|---|---|---|
| Young | Older | Young | Older | Young | Older | |
| Peak PFJ Stress (MPa) | 1.09 (0.35) | 1.21 (0.43) | 1.06 (0.36) | 1.26 (0.38) | 1.06 (0.31) | 1.20 (0.42) |
| PFJ Stress–time Integral (MPa * % stance) *† | 29.51 (21.38) | 62.36 (22.89) | 37.55 (26.86) | 67.64 (22.04) | 29.53 (26.80) | 61.33 (23.43) |
| PFJ Stress Time of Peak (% stance) *# | 26.33 (3.26) | 44.00 (24.38) | 28.00 (3.54) | 60.00 (25.60) | 27.58 (3.48) | 41.83 (21.97) |
| Peak PFJ Reaction Force (N) | 166.13 (52.76) | 184.40 (64.68) | 162.03 (54.47) | 192.18 (57.53) | 160.90 (46.89) | 182.58 (63.23) |
| PFJ Reaction Force Impulse (N * % stance) *† | 4496.51 (3249.06) | 9488.27 (3481.29) | 5720.80 (4081.43) | 10,294.22 (3352.46) | 4498.86 (4072.37) | 9330.84 (3561.67) |
| PFJ Contact Area Range (mm2) † | 0.54 (0.057) | 0.52 (0.058) | 0.63 (0.075) | 0.60 (0.062) | 0.52 (0.047) | 0.50 (0.070) |
| PFJ Contact Area Mean (mm2) † | 152.11 (0.071) | 152.12 (0.12) | 152.16 (0.084) | 152.18 (0.10) | 152.12 (0.076) | 152.12 (0.91) |
* Denotes a significant (p < 0.05) main effect of age. † Denotes a significant (p < 0.05) main effect of surface. # Denotes a significant (p < 0.05) interaction between age and surface.
Table 3.
Mean (SD) for knee flexion biomechanics during stair ascent and descent tasks for young and older adults on each surface (normal, uneven, and slick).
Table 3.
Mean (SD) for knee flexion biomechanics during stair ascent and descent tasks for young and older adults on each surface (normal, uneven, and slick).
| Normal | Uneven | Slick | ||||
|---|---|---|---|---|---|---|
| Young | Older | Young | Older | Young | Older | |
| Stair Ascent | ||||||
| Peak Knee Flexion Angle (deg) † | 51.82 (4.81) | 49.88 (8.71) | 58.71 (5.20) | 55.63 (6.89) | 51.37 (5.13) | 48.65 (8.69) |
| Knee Flexion at Peak PFJ Stress (deg) *# | 44.99 (4.86) | 39.18 (7.15) | 49.79 (5.63) | 37.42 (8.93) | 44.88 (4.76) | 38.82 (7.22) |
| Peak Knee Extension Moment (Nm/kg·m) † | 0.77 (0.13) | 0.70 (0.15) | 0.81 (0.14) | 0.73 (0.12) | 0.75 (0.13) | 0.68 (0.12) |
| Stair Descent | ||||||
| Peak Knee Flexion Angle (deg) * | 82.57 (5.04) | 76.32 (5.67) | 83.09 (7.96) | 76.28 (7.45) | 80.28 (7.36) | 75.17 (5.22) |
| Knee Flexion at Peak PFJ Stress (deg) † | 39.14 (11.49) | 37.52 (11.17) | 43.91 (12.91) | 41.80 (12.40) | 38.89 (11.41) | 44.51 (8.87) |
| Peak Knee Extension Moment (Nm/kg·m) † | 0.73 (0.17) | 0.72 (0.15) | 0.81 (0.16) | 0.80 (0.17) | 0.73 (0.14) | 0.76 (0.13) |
* Denotes a significant (p < 0.05) main effect of age. † Denotes a significant (p < 0.05) main effect of surface. # Denotes a significant (p < 0.05) interaction between age and surface.
Table 4.
Mean (SD) for PFJ measures during stair descent for young and older adults on each surface (normal, uneven, and slick).
Table 4.
Mean (SD) for PFJ measures during stair descent for young and older adults on each surface (normal, uneven, and slick).
| Normal | Uneven | Slick | ||||
|---|---|---|---|---|---|---|
| Young | Older | Young | Older | Young | Older | |
| Peak PFJ Stress (MPa) | 1.08 (0.30) | 1.32 (0.59) | 1.07 (0.27) | 1.28 (0.60) | 1.12 (0.36) | 1.22 (0.51) |
| PFJ Stress–time Integral (MPa * % stance) † | 48.83 (12.56) | 62.68 (30.59) | 53.28 (18.93) | 72.02 (40.54) | 46.46 (15.85) | 60.53 (28.51) |
| PFJ Stress Time of Peak (% stance) | 46.75 (30.32) | 46.50 (29.08) | 51.75 (31.37) | 54.08 (27.00) | 48.58 (30.34) | 61.00 (27.82) |
| Peak PFJ Reaction Force (N) | 164.88 (46.29) | 201.32 (89.96) | 162.38 (41.64) | 194.19 (90.95) | 171.12 (55.12) | 185.88 (77.55) |
| PFJ Reaction Force Impulse (N * % stance) † | 7435.62 (1909.59) | 9538.78 (4649.09) | 8112.80 (2879.85) | 10,962.25 (6163.99) | 7074.70 (2412.22) | 9213.35 (4335.42) |
| PFJ Contact Area Range (mm2) * | 1.07 (0.067) | 1.01 (0.060) | 1.07 (0.11) | 0.96 (0.11) | 1.03 (0.11) | 0.98 (0.056) |
| PFJ Contact Area Mean (mm2) † | 152.20 (0.065) | 152.15 (0.10) | 152.22 (0.077) | 152.20 (0.11) | 152.19 (0.084) | 152.16 (0.085) |
* Denotes a significant (p < 0.05) main effect of age. † Denotes a significant (p < 0.05) main effect of surface.
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MDPI and ACS Style
Hunt, N.L.; Holcomb, A.E.; Fitzpatrick, C.K.; Brown, T.N. Effects of Aging on Patellofemoral Joint Stress during Stair Negotiation on Challenging Surfaces. Biomechanics 2024, 4, 507-519. https://doi.org/10.3390/biomechanics4030036
AMA Style
Hunt NL, Holcomb AE, Fitzpatrick CK, Brown TN. Effects of Aging on Patellofemoral Joint Stress during Stair Negotiation on Challenging Surfaces. Biomechanics. 2024; 4(3):507-519. https://doi.org/10.3390/biomechanics4030036
Chicago/Turabian StyleHunt, Nicholas L., Amy E. Holcomb, Clare K. Fitzpatrick, and Tyler N. Brown. 2024. "Effects of Aging on Patellofemoral Joint Stress during Stair Negotiation on Challenging Surfaces" Biomechanics 4, no. 3: 507-519. https://doi.org/10.3390/biomechanics4030036
APA StyleHunt, N. L., Holcomb, A. E., Fitzpatrick, C. K., & Brown, T. N. (2024). Effects of Aging on Patellofemoral Joint Stress during Stair Negotiation on Challenging Surfaces. Biomechanics, 4(3), 507-519. https://doi.org/10.3390/biomechanics4030036
